2 days ago
Remote, IrelandSenior
Responsibilities
- Design and manage CI/CD and deployment pipelines for AWS-native and Kubernetes-based applications.
- Advise product teams on deployment requirements and cloud and container best practices.
- Manage cloud infrastructure, DevOps infrastructure, pipelines, and delivery processes.
- Automate code changes, builds, testing, and analysis using CI tools.
- Monitor post-release performance and develop automated alerting and observability systems.
- Implement DevSecOps controls including application, dependency, secrets, and container scanning.
- Implement IAM, network segmentation, encryption, secrets management, Kubernetes hardening, policy-as-code, admission controls, and runtime protection.
- Support vulnerability management, incident response, audit readiness, and SOC 2 and ISO 27001 compliance efforts.
- Use AI-assisted tools and AI/ML capabilities for pipeline development, troubleshooting, incident analysis, anomaly detection, alert reduction, and root-cause analysis.
- Build and operate infrastructure and deployment pipelines for AI/ML and LLM workloads, including model serving and GPU-enabled clusters.
- Establish responsible-AI guardrails covering data privacy, access controls, and review of AI-generated code and configuration.
Requirements
- At least 8 years of experience maintaining high-traffic applications and complex technical infrastructure.
- Proven experience supporting cloud environments and applying AWS Well-Architected principles.
- Hands-on experience with Kubernetes clusters and customer cloud environments.
- Experience with AWS services, infrastructure-as-code, CI/CD tools, monitoring and logging platforms, cloud networking, and software development lifecycle processes.
- Experience with DevSecOps, AWS security services, container and software supply-chain security, security scanning, Kubernetes security, and secrets management.
- Practical experience using AI coding and operations assistants such as GitHub Copilot, Claude, or Amazon Q.
- Understanding of deploying and operating AI/ML workloads using technologies such as Amazon Bedrock, SageMaker, and model serving on Kubernetes.
- Awareness of AI-specific risks including prompt injection, data leakage, and insecure AI-generated code.
- Preferred experience with Python or Bash, Linux administration, HTTP/2, microservice and serverless architectures, GitOps tooling, internal AI-enabled DevOps tooling, and databases.
- Relevant certifications such as AWS Certified DevOps Engineer, AWS Security Specialty, CKA, or CKS are preferred.
Benefits
- Remote-friendly work environment with a collaborative global team.
- Opportunity to work on scientific software products and infrastructure supporting customers in more than 180 countries.
- Equal opportunity workplace focused on inclusion, support, and connection.
Tech Stack
Argo CDAWSBashDatadogGitHub ActionsGrafanaJenkinsKubernetesLinuxMongoDBMySQLOctopus DeployPostgreSQLPrometheusPythonSonarQubeTeamCityTerraform
Categories
About Dotmatics
Dotmatics builds cloud-based R&D scientific software that unifies biology, chemistry, and data management workflows for biopharma, chemicals/materials companies, and academic labs; products include Luma, ELN, GraphPad Prism, Geneious, SnapGene, Protein Metrics, and LabArchives. The company sells SaaS and enterprise licenses for data integration, analysis, and decision support, is headquartered in Boston, and operates as a Siemens company following its acquisition.